Pandas Profiling Report

Dataset statistics

Number of variables	22
Number of observations	25252
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	4.2 MiB
Average record size in memory	176.0 B

Variable types

Numeric	16
Categorical	6

Alerts

`in_transit_qty` is highly correlated with `forecast_6_month` and 6 other fields	High correlation
`forecast_3_month` is highly correlated with `forecast_6_month` and 5 other fields	High correlation
`forecast_6_month` is highly correlated with `in_transit_qty` and 6 other fields	High correlation
`forecast_9_month` is highly correlated with `in_transit_qty` and 6 other fields	High correlation
`sales_1_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_3_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_6_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_9_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`min_bank` is highly correlated with `in_transit_qty` and 4 other fields	High correlation
`perf_6_month_avg` is highly correlated with `perf_12_month_avg`	High correlation
`perf_12_month_avg` is highly correlated with `perf_6_month_avg`	High correlation
`in_transit_qty` is highly correlated with `forecast_3_month` and 7 other fields	High correlation
`forecast_3_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`forecast_6_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`forecast_9_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_1_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_3_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_6_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_9_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`min_bank` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`perf_6_month_avg` is highly correlated with `perf_12_month_avg`	High correlation
`perf_12_month_avg` is highly correlated with `perf_6_month_avg`	High correlation
`forecast_3_month` is highly correlated with `forecast_6_month` and 3 other fields	High correlation
`forecast_6_month` is highly correlated with `forecast_3_month` and 5 other fields	High correlation
`forecast_9_month` is highly correlated with `forecast_3_month` and 5 other fields	High correlation
`sales_1_month` is highly correlated with `forecast_3_month` and 6 other fields	High correlation
`sales_3_month` is highly correlated with `forecast_3_month` and 6 other fields	High correlation
`sales_6_month` is highly correlated with `forecast_6_month` and 5 other fields	High correlation
`sales_9_month` is highly correlated with `forecast_6_month` and 5 other fields	High correlation
`min_bank` is highly correlated with `sales_1_month` and 3 other fields	High correlation
`perf_6_month_avg` is highly correlated with `perf_12_month_avg`	High correlation
`perf_12_month_avg` is highly correlated with `perf_6_month_avg`	High correlation
`lead_time` is highly correlated with `perf_6_month_avg` and 1 other fields	High correlation
`in_transit_qty` is highly correlated with `forecast_3_month` and 7 other fields	High correlation
`forecast_3_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`forecast_6_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`forecast_9_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_1_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_3_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_6_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`sales_9_month` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`min_bank` is highly correlated with `in_transit_qty` and 7 other fields	High correlation
`perf_6_month_avg` is highly correlated with `lead_time` and 1 other fields	High correlation
`perf_12_month_avg` is highly correlated with `lead_time` and 1 other fields	High correlation
`national_inv` is highly skewed (γ1 = 21.55281716)	Skewed
`pieces_past_due` is highly skewed (γ1 = 29.84564693)	Skewed
`sku` has unique values	Unique
`national_inv` has 2555 (10.1%) zeros	Zeros
`in_transit_qty` has 20266 (80.3%) zeros	Zeros
`forecast_3_month` has 14959 (59.2%) zeros	Zeros
`forecast_6_month` has 13521 (53.5%) zeros	Zeros
`forecast_9_month` has 12806 (50.7%) zeros	Zeros
`sales_1_month` has 13220 (52.4%) zeros	Zeros
`sales_3_month` has 10224 (40.5%) zeros	Zeros
`sales_6_month` has 8629 (34.2%) zeros	Zeros
`sales_9_month` has 7836 (31.0%) zeros	Zeros
`min_bank` has 13123 (52.0%) zeros	Zeros
`pieces_past_due` has 24582 (97.3%) zeros	Zeros
`perf_6_month_avg` has 671 (2.7%) zeros	Zeros
`perf_12_month_avg` has 547 (2.2%) zeros	Zeros
`local_bo_qty` has 24510 (97.1%) zeros	Zeros

Reproduction

Analysis started	2021-10-22 17:21:02.856254
Analysis finished	2021-10-22 17:21:47.144382
Duration	44.29 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

sku
Real number (ℝ_≥0)

UNIQUE

Distinct	25252
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	42161.59409

Minimum	1
Maximum	84170
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	197.4 KiB

Quantile statistics

Minimum	1
5-th percentile	4271.75
Q1	20988.5
median	42372
Q3	63313.25
95-th percentile	79838.35
Maximum	84170
Range	84169
Interquartile range (IQR)	42324.75

Descriptive statistics

Standard deviation	24291.90894
Coefficient of variation (CV)	0.5761620135
Kurtosis	-1.206304855
Mean	42161.59409
Median Absolute Deviation (MAD)	21140
Skewness	-0.009788689894
Sum	1064664574
Variance	590096840.1
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2047	1	< 0.1%
60951	1	< 0.1%
36379	1	< 0.1%
42526	1	< 0.1%
73257	1	< 0.1%
13868	1	< 0.1%
11823	1	< 0.1%
56881	1	< 0.1%
52787	1	< 0.1%
11243	1	< 0.1%
Other values (25242)	25242	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	1	< 0.1%
3	1	< 0.1%
4	1	< 0.1%
6	1	< 0.1%
8	1	< 0.1%
12	1	< 0.1%
13	1	< 0.1%
14	1	< 0.1%
15	1	< 0.1%
17	1	< 0.1%

Value	Count	Frequency (%)
84170	1	< 0.1%
84168	1	< 0.1%
84155	1	< 0.1%
84149	1	< 0.1%
84148	1	< 0.1%
84144	1	< 0.1%
84139	1	< 0.1%
84137	1	< 0.1%
84135	1	< 0.1%
84132	1	< 0.1%

national_inv
Real number (ℝ)

SKEWED
ZEROS

Distinct	1616
Distinct (%)	6.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	213.4758435

Minimum	-1238
Maximum	73138
Zeros	2555
Zeros (%)	10.1%
Negative	305
Negative (%)	1.2%
Memory size	197.4 KiB

Quantile statistics

Minimum	-1238
5-th percentile	0
Q1	3
median	10
Q3	55
95-th percentile	592
Maximum	73138
Range	74376
Interquartile range (IQR)	52

Descriptive statistics

Standard deviation	1632.760586
Coefficient of variation (CV)	7.648455952
Kurtosis	621.4059689
Mean	213.4758435
Median Absolute Deviation (MAD)	9
Skewness	21.55281716
Sum	5390692
Variance	2665907.131
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	2555	10.1%
2	1781	7.1%
3	1478	5.9%
1	1162	4.6%
4	1127	4.5%
5	967	3.8%
6	813	3.2%
7	700	2.8%
10	666	2.6%
8	564	2.2%
Other values (1606)	13439	53.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-1238	1	< 0.1%
-134	1	< 0.1%
-130	1	< 0.1%
-100	3	< 0.1%
-98	1	< 0.1%
-95	1	< 0.1%
-87	1	< 0.1%
-85	1	< 0.1%
-82	1	< 0.1%
-75	1	< 0.1%

Value	Count	Frequency (%)
73138	1	< 0.1%
69500	1	< 0.1%
60225	1	< 0.1%
46170	1	< 0.1%
45867	1	< 0.1%
42405	1	< 0.1%
41785	1	< 0.1%
41612	1	< 0.1%
41218	1	< 0.1%
39592	1	< 0.1%

lead_time
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	22
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.89806748

Minimum	0
Maximum	28
Zeros	183
Zeros (%)	0.7%
Negative	0
Negative (%)	0.0%
Memory size	197.4 KiB

Quantile statistics

Minimum	0
5-th percentile	2
Q1	3
median	8
Q3	8
95-th percentile	12
Maximum	28
Range	28
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	3.520616682
Coefficient of variation (CV)	0.5103772458
Kurtosis	-0.6154051589
Mean	6.89806748
Median Absolute Deviation (MAD)	1
Skewness	-0.03550105442
Sum	174190
Variance	12.39474182
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=22)

Value	Count	Frequency (%)
8	10848	43.0%
2	5853	23.2%
12	3218	12.7%
4	2013	8.0%
9	1925	7.6%
3	300	1.2%
10	216	0.9%
0	183	0.7%
14	151	0.6%
16	129	0.5%
Other values (12)	416	1.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	183	0.7%
2	5853	23.2%
3	300	1.2%
4	2013	8.0%
5	77	0.3%
6	103	0.4%
7	5	< 0.1%
8	10848	43.0%
9	1925	7.6%
10	216	0.9%

Value	Count	Frequency (%)
28	1	< 0.1%
25	1	< 0.1%
22	3	< 0.1%
20	10	< 0.1%
18	2	< 0.1%
17	53	0.2%
16	129	0.5%
15	68	0.3%
14	151	0.6%
13	66	0.3%

in_transit_qty
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	555
Distinct (%)	2.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	18.03884841

Minimum	0
Maximum	3726
Zeros	20266
Zeros (%)	80.3%
Negative	0
Negative (%)	0.0%
Memory size	197.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	57
Maximum	3726
Range	3726
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	126.4874591
Coefficient of variation (CV)	7.011947559
Kurtosis	312.9411674
Mean	18.03884841
Median Absolute Deviation (MAD)	0
Skewness	15.36020216
Sum	455517
Variance	15999.0773
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	20266	80.3%
1	583	2.3%
2	364	1.4%
3	265	1.0%
4	228	0.9%
6	182	0.7%
5	176	0.7%
8	133	0.5%
10	116	0.5%
12	112	0.4%
Other values (545)	2827	11.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	20266	80.3%
1	583	2.3%
2	364	1.4%
3	265	1.0%
4	228	0.9%
5	176	0.7%
6	182	0.7%
7	106	0.4%
8	133	0.5%
9	90	0.4%

Value	Count	Frequency (%)
3726	1	< 0.1%
3722	1	< 0.1%
3644	1	< 0.1%
3550	1	< 0.1%
3500	1	< 0.1%
3360	1	< 0.1%
3128	1	< 0.1%
3080	1	< 0.1%
3072	1	< 0.1%
2920	1	< 0.1%

forecast_3_month
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	1008
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	89.19855853

Minimum	0
Maximum	16300
Zeros	14959
Zeros (%)	59.2%
Negative	0
Negative (%)	0.0%
Memory size	197.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	12
95-th percentile	360
Maximum	16300
Range	16300
Interquartile range (IQR)	12

Descriptive statistics

Standard deviation	515.0172037
Coefficient of variation (CV)	5.773828772
Kurtosis	300.4407618
Mean	89.19855853
Median Absolute Deviation (MAD)	0
Skewness	14.611488
Sum	2252442
Variance	265242.7201
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	14959	59.2%
1	601	2.4%
2	549	2.2%
5	436	1.7%
4	409	1.6%
3	373	1.5%
10	325	1.3%
6	293	1.2%
12	259	1.0%
8	225	0.9%
Other values (998)	6823	27.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	14959	59.2%
1	601	2.4%
2	549	2.2%
3	373	1.5%
4	409	1.6%
5	436	1.7%
6	293	1.2%
7	206	0.8%
8	225	0.9%
9	153	0.6%

Value	Count	Frequency (%)
16300	1	< 0.1%
15456	1	< 0.1%
15343	1	< 0.1%
15000	1	< 0.1%
14400	1	< 0.1%
13902	1	< 0.1%
13015	1	< 0.1%
10659	1	< 0.1%
10648	1	< 0.1%
10500	1	< 0.1%

forecast_6_month
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	1344
Distinct (%)	5.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	164.663789

Minimum	0
Maximum	28000
Zeros	13521
Zeros (%)	53.5%
Negative	0
Negative (%)	0.0%
Memory size	197.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	26
95-th percentile	636.9
Maximum	28000
Range	28000
Interquartile range (IQR)	26

Descriptive statistics

Standard deviation	941.8269453
Coefficient of variation (CV)	5.719696789
Kurtosis	293.4173668
Mean	164.663789
Median Absolute Deviation (MAD)	0
Skewness	14.52443836
Sum	4158090
Variance	887037.9949
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	13521	53.5%
1	514	2.0%
2	475	1.9%
3	437	1.7%
4	382	1.5%
5	360	1.4%
6	348	1.4%
10	314	1.2%
8	275	1.1%
7	270	1.1%
Other values (1334)	8356	33.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	13521	53.5%
1	514	2.0%
2	475	1.9%
3	437	1.7%
4	382	1.5%
5	360	1.4%
6	348	1.4%
7	270	1.1%
8	275	1.1%
9	157	0.6%

Value	Count	Frequency (%)
28000	1	< 0.1%
27048	1	< 0.1%
26880	1	< 0.1%
26400	1	< 0.1%
26068	1	< 0.1%
25740	1	< 0.1%
25057	1	< 0.1%
23320	1	< 0.1%
21000	1	< 0.1%
20030	1	< 0.1%

forecast_9_month
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	1604
Distinct (%)	6.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	243.2605734

Minimum	0
Maximum	42000
Zeros	12806
Zeros (%)	50.7%
Negative	0
Negative (%)	0.0%
Memory size	197.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	40
95-th percentile	941.45
Maximum	42000
Range	42000
Interquartile range (IQR)	40

Descriptive statistics

Standard deviation	1411.522973
Coefficient of variation (CV)	5.802514371
Kurtosis	310.8687612
Mean	243.2605734
Median Absolute Deviation (MAD)	0
Skewness	14.9954653
Sum	6142816
Variance	1992397.104
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	12806	50.7%
1	448	1.8%
2	444	1.8%
3	405	1.6%
5	381	1.5%
4	362	1.4%
6	337	1.3%
10	331	1.3%
8	296	1.2%
12	259	1.0%
Other values (1594)	9183	36.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	12806	50.7%
1	448	1.8%
2	444	1.8%
3	405	1.6%
4	362	1.4%
5	381	1.5%
6	337	1.3%
7	216	0.9%
8	296	1.2%
9	185	0.7%

Value	Count	Frequency (%)
42000	1	< 0.1%
41340	1	< 0.1%
40782	1	< 0.1%
40020	1	< 0.1%
38400	1	< 0.1%
37296	1	< 0.1%
36724	1	< 0.1%
36280	1	< 0.1%
35383	1	< 0.1%
32775	1	< 0.1%

sales_1_month
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	679
Distinct (%)	2.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	26.53136385

Minimum	0
Maximum	4907
Zeros	13220
Zeros (%)	52.4%
Negative	0
Negative (%)	0.0%
Memory size	197.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	6
95-th percentile	102
Maximum	4907
Range	4907
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	142.1103457
Coefficient of variation (CV)	5.356315135
Kurtosis	245.4609087
Mean	26.53136385
Median Absolute Deviation (MAD)	0
Skewness	13.15885423
Sum	669970
Variance	20195.35037
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	13220	52.4%
1	2361	9.3%
2	1331	5.3%
3	787	3.1%
4	684	2.7%
5	540	2.1%
6	444	1.8%
7	356	1.4%
8	346	1.4%
9	275	1.1%
Other values (669)	4908	19.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	13220	52.4%
1	2361	9.3%
2	1331	5.3%
3	787	3.1%
4	684	2.7%
5	540	2.1%
6	444	1.8%
7	356	1.4%
8	346	1.4%
9	275	1.1%

Value	Count	Frequency (%)
4907	1	< 0.1%
3971	1	< 0.1%
3801	1	< 0.1%
3480	1	< 0.1%
3108	1	< 0.1%
3077	1	< 0.1%
2966	1	< 0.1%
2960	1	< 0.1%
2900	1	< 0.1%
2814	1	< 0.1%

sales_3_month
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	1186
Distinct (%)	4.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	83.71748772

Minimum	0
Maximum	14464
Zeros	10224
Zeros (%)	40.5%
Negative	0
Negative (%)	0.0%
Memory size	197.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	2
Q3	18
95-th percentile	332.9
Maximum	14464
Range	14464
Interquartile range (IQR)	18

Descriptive statistics

Standard deviation	438.4914875
Coefficient of variation (CV)	5.237752582
Kurtosis	242.0126248
Mean	83.71748772
Median Absolute Deviation (MAD)	2
Skewness	13.03895944
Sum	2114034
Variance	192274.7846
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	10224	40.5%
1	1987	7.9%
2	1268	5.0%
3	906	3.6%
4	666	2.6%
5	552	2.2%
6	478	1.9%
7	395	1.6%
8	337	1.3%
10	311	1.2%
Other values (1176)	8128	32.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	10224	40.5%
1	1987	7.9%
2	1268	5.0%
3	906	3.6%
4	666	2.6%
5	552	2.2%
6	478	1.9%
7	395	1.6%
8	337	1.3%
9	308	1.2%

Value	Count	Frequency (%)
14464	1	< 0.1%
11998	1	< 0.1%
11280	1	< 0.1%
11277	1	< 0.1%
10242	1	< 0.1%
10211	1	< 0.1%
9992	1	< 0.1%
9731	1	< 0.1%
9470	1	< 0.1%
8930	1	< 0.1%

sales_6_month
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	1627
Distinct (%)	6.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	165.1147236

Minimum	0
Maximum	26512
Zeros	8629
Zeros (%)	34.2%
Negative	0
Negative (%)	0.0%
Memory size	197.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	4
Q3	36
95-th percentile	644.45
Maximum	26512
Range	26512
Interquartile range (IQR)	36

Descriptive statistics

Standard deviation	874.1210956
Coefficient of variation (CV)	5.294022705
Kurtosis	248.0567378
Mean	165.1147236
Median Absolute Deviation (MAD)	4
Skewness	13.28757677
Sum	4169477
Variance	764087.6899
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	8629	34.2%
1	1827	7.2%
2	1198	4.7%
3	807	3.2%
4	686	2.7%
5	493	2.0%
6	469	1.9%
7	378	1.5%
8	344	1.4%
9	316	1.3%
Other values (1617)	10105	40.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	8629	34.2%
1	1827	7.2%
2	1198	4.7%
3	807	3.2%
4	686	2.7%
5	493	2.0%
6	469	1.9%
7	378	1.5%
8	344	1.4%
9	316	1.3%

Value	Count	Frequency (%)
26512	1	< 0.1%
25630	1	< 0.1%
22904	1	< 0.1%
22397	1	< 0.1%
22392	1	< 0.1%
22152	1	< 0.1%
20514	1	< 0.1%
18902	1	< 0.1%
18678	1	< 0.1%
17883	1	< 0.1%

sales_9_month
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	1937
Distinct (%)	7.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	249.6094171

Minimum	0
Maximum	42410
Zeros	7836
Zeros (%)	31.0%
Negative	0
Negative (%)	0.0%
Memory size	197.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	6
Q3	52
95-th percentile	970.45
Maximum	42410
Range	42410
Interquartile range (IQR)	52

Descriptive statistics

Standard deviation	1339.618948
Coefficient of variation (CV)	5.36686061
Kurtosis	261.88017
Mean	249.6094171
Median Absolute Deviation (MAD)	6
Skewness	13.63280407
Sum	6303137
Variance	1794578.927
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	7836	31.0%
1	1677	6.6%
2	1117	4.4%
3	827	3.3%
4	638	2.5%
5	521	2.1%
6	430	1.7%
8	362	1.4%
7	351	1.4%
9	318	1.3%
Other values (1927)	11175	44.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	7836	31.0%
1	1677	6.6%
2	1117	4.4%
3	827	3.3%
4	638	2.5%
5	521	2.1%
6	430	1.7%
7	351	1.4%
8	362	1.4%
9	318	1.3%

Value	Count	Frequency (%)
42410	1	< 0.1%
39691	1	< 0.1%
37872	1	< 0.1%
33333	1	< 0.1%
32978	1	< 0.1%
31833	1	< 0.1%
31723	1	< 0.1%
30596	1	< 0.1%
30298	1	< 0.1%
28258	1	< 0.1%

min_bank
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	644
Distinct (%)	2.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	26.62422778

Minimum	0
Maximum	3386
Zeros	13123
Zeros (%)	52.0%
Negative	0
Negative (%)	0.0%
Memory size	197.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	3
95-th percentile	115
Maximum	3386
Range	3386
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	134.0587735
Coefficient of variation (CV)	5.035217344
Kurtosis	199.9160793
Mean	26.62422778
Median Absolute Deviation (MAD)	0
Skewness	12.23090191
Sum	672315
Variance	17971.75475
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	13123	52.0%
1	3732	14.8%
2	1618	6.4%
3	541	2.1%
4	340	1.3%
5	225	0.9%
6	178	0.7%
7	154	0.6%
8	131	0.5%
13	121	0.5%
Other values (634)	5089	20.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	13123	52.0%
1	3732	14.8%
2	1618	6.4%
3	541	2.1%
4	340	1.3%
5	225	0.9%
6	178	0.7%
7	154	0.6%
8	131	0.5%
9	97	0.4%

Value	Count	Frequency (%)
3386	1	< 0.1%
3361	1	< 0.1%
3094	1	< 0.1%
3045	1	< 0.1%
2986	1	< 0.1%
2936	1	< 0.1%
2890	1	< 0.1%
2859	1	< 0.1%
2845	1	< 0.1%
2777	1	< 0.1%

potential_issue
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	197.4 KiB

0	25232
1	20

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	25232	99.9%
1	20	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	25232	99.9%
1	20	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

pieces_past_due
Real number (ℝ_≥0)

SKEWED
ZEROS

Distinct	111
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.9297877396

Minimum	0
Maximum	720
Zeros	24582
Zeros (%)	97.3%
Negative	0
Negative (%)	0.0%
Memory size	197.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	720
Range	720
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	13.40581047
Coefficient of variation (CV)	14.41814072
Kurtosis	1154.485738
Mean	0.9297877396
Median Absolute Deviation (MAD)	0
Skewness	29.84564693
Sum	23479
Variance	179.7157544
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	24582	97.3%
1	92	0.4%
2	45	0.2%
3	37	0.1%
4	28	0.1%
5	24	0.1%
10	24	0.1%
6	22	0.1%
18	21	0.1%
12	19	0.1%
Other values (101)	358	1.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	24582	97.3%
1	92	0.4%
2	45	0.2%
3	37	0.1%
4	28	0.1%
5	24	0.1%
6	22	0.1%
7	16	0.1%
8	12	< 0.1%
9	12	< 0.1%

Value	Count	Frequency (%)
720	1	< 0.1%
600	3	< 0.1%
540	1	< 0.1%
514	1	< 0.1%
400	1	< 0.1%
350	1	< 0.1%
336	1	< 0.1%
326	1	< 0.1%
325	1	< 0.1%
316	1	< 0.1%

perf_6_month_avg
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	101
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.7715622525

Minimum	0
Maximum	1
Zeros	671
Zeros (%)	2.7%
Negative	0
Negative (%)	0.0%
Memory size	197.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0.19
Q1	0.69
median	0.83
Q3	0.97
95-th percentile	1
Maximum	1
Range	1
Interquartile range (IQR)	0.28

Descriptive statistics

Standard deviation	0.2446894816
Coefficient of variation (CV)	0.3171351124
Kurtosis	1.858815432
Mean	0.7715622525
Median Absolute Deviation (MAD)	0.14
Skewness	-1.500968051
Sum	19483.49
Variance	0.05987294242
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.99	2254	8.9%
1	1991	7.9%
0.73	1750	6.9%
0.98	1340	5.3%
0.97	994	3.9%
0.78	712	2.8%
0.95	690	2.7%
0	671	2.7%
0.82	665	2.6%
0.96	646	2.6%
Other values (91)	13539	53.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	671	2.7%
0.01	11	< 0.1%
0.02	18	0.1%
0.03	11	< 0.1%
0.04	17	0.1%
0.05	36	0.1%
0.06	26	0.1%
0.07	41	0.2%
0.08	33	0.1%
0.09	34	0.1%

Value	Count	Frequency (%)
1	1991	7.9%
0.99	2254	8.9%
0.98	1340	5.3%
0.97	994	3.9%
0.96	646	2.6%
0.95	690	2.7%
0.94	567	2.2%
0.93	535	2.1%
0.92	329	1.3%
0.91	477	1.9%

perf_12_month_avg
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	101
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.768751386

Minimum	0
Maximum	1
Zeros	547
Zeros (%)	2.2%
Negative	0
Negative (%)	0.0%
Memory size	197.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0.23
Q1	0.68
median	0.82
Q3	0.95
95-th percentile	0.99
Maximum	1
Range	1
Interquartile range (IQR)	0.27

Descriptive statistics

Standard deviation	0.2354178177
Coefficient of variation (CV)	0.3062340075
Kurtosis	2.008194421
Mean	0.768751386
Median Absolute Deviation (MAD)	0.14
Skewness	-1.526624409
Sum	19412.51
Variance	0.0554215489
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.99	2101	8.3%
0.78	1818	7.2%
0.98	1464	5.8%
0.97	1095	4.3%
0.96	986	3.9%
0.66	936	3.7%
0.95	737	2.9%
0.9	729	2.9%
0.82	656	2.6%
0.79	635	2.5%
Other values (91)	14095	55.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	547	2.2%
0.01	28	0.1%
0.02	13	0.1%
0.03	9	< 0.1%
0.04	20	0.1%
0.05	16	0.1%
0.06	11	< 0.1%
0.07	19	0.1%
0.08	17	0.1%
0.09	47	0.2%

Value	Count	Frequency (%)
1	621	2.5%
0.99	2101	8.3%
0.98	1464	5.8%
0.97	1095	4.3%
0.96	986	3.9%
0.95	737	2.9%
0.94	616	2.4%
0.93	545	2.2%
0.92	466	1.8%
0.91	410	1.6%

local_bo_qty
Real number (ℝ_≥0)

ZEROS

Distinct	80
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.3449231744

Minimum	0
Maximum	131
Zeros	24510
Zeros (%)	97.1%
Negative	0
Negative (%)	0.0%
Memory size	197.4 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	131
Range	131
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	3.936064409
Coefficient of variation (CV)	11.41142347
Kurtosis	384.7562865
Mean	0.3449231744
Median Absolute Deviation (MAD)	0
Skewness	17.94419664
Sum	8710
Variance	15.49260303
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	24510	97.1%
1	214	0.8%
2	107	0.4%
3	55	0.2%
4	42	0.2%
6	36	0.1%
5	25	0.1%
10	22	0.1%
8	20	0.1%
7	19	0.1%
Other values (70)	202	0.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	24510	97.1%
1	214	0.8%
2	107	0.4%
3	55	0.2%
4	42	0.2%
5	25	0.1%
6	36	0.1%
7	19	0.1%
8	20	0.1%
9	10	< 0.1%

Value	Count	Frequency (%)
131	1	< 0.1%
124	1	< 0.1%
113	1	< 0.1%
100	4	< 0.1%
99	1	< 0.1%
93	1	< 0.1%
92	1	< 0.1%
91	1	< 0.1%
90	1	< 0.1%
89	1	< 0.1%

deck_risk
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	197.4 KiB

0	20643
1	4609

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	1
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
0	20643	81.7%
1	4609	18.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	20643	81.7%
1	4609	18.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

oe_constraint
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	197.4 KiB

0	25243
1	9

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	25243	> 99.9%
1	9	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	25243	> 99.9%
1	9	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

ppap_risk
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	197.4 KiB

0	22135
1	3117

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	22135	87.7%
1	3117	12.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	22135	87.7%
1	3117	12.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

stop_auto_buy
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	197.4 KiB

1	24798
0	454

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	24798	98.2%
0	454	1.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	24798	98.2%
0	454	1.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

rev_stop
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	197.4 KiB

0	25246
1	6

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	25246	> 99.9%
1	6	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	25246	> 99.9%
1	6	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	sku	national_inv	lead_time	in_transit_qty	forecast_3_month	forecast_6_month	forecast_9_month	sales_1_month	sales_3_month	sales_6_month	sales_9_month	min_bank	potential_issue	pieces_past_due	perf_6_month_avg	perf_12_month_avg	local_bo_qty	deck_risk	stop_auto_buy
0	1	6	12	0	0	0	0	0	0	0	0	0	0	0	0.57	0.68	0	0	1
1	3	0	2	8	18	30	42	10	30	58	83	3	0	0	0.93	0.94	0	0	1
2	4	6	8	0	0	0	0	0	0	0	0	0	0	0	0.87	0.88	0	1	1
3	6	10	14	0	0	0	0	0	1	1	1	0	0	0	0.00	0.10	0	1	1
4	8	1489	8	0	0	0	0	1	4	20	22	0	0	0	0.90	0.94	0	0	1
5	12	3	8	0	0	0	0	0	0	0	0	1	0	0	0.37	0.34	0	0	1
6	13	1	2	0	11	17	24	3	10	19	20	0	0	0	0.99	0.99	0	1	1
7	14	170	8	47	156	296	436	53	160	294	482	129	0	0	0.62	0.68	0	0	1
8	15	9	8	0	220	320	380	44	109	189	289	42	1	20	1.00	0.89	2	0	1
9	17	1	8	0	12	20	24	4	10	12	18	2	0	0	0.97	0.97	0	0	1

Last rows

	sku	national_inv	lead_time	in_transit_qty	forecast_3_month	forecast_6_month	forecast_9_month	sales_1_month	sales_3_month	sales_6_month	sales_9_month	min_bank	perf_6_month_avg	perf_12_month_avg	deck_risk	ppap_risk	stop_auto_buy
25242	84132	175	8	0	0	0	0	9	38	66	83	25	0.96	0.97	0	0	1
25243	84135	1	8	0	6	10	14	1	4	8	9	0	0.37	0.34	0	0	1
25244	84137	2	12	0	3	5	7	1	3	4	6	0	0.92	0.94	0	0	1
25245	84139	304	8	44	352	682	946	118	366	747	1135	114	0.99	0.97	0	0	1
25246	84144	12	2	0	5	15	20	2	5	19	39	0	0.98	0.99	0	0	1
25247	84148	12	8	0	0	0	0	1	4	9	16	0	0.83	0.86	0	0	1
25248	84149	322	12	0	0	80	239	20	189	401	642	46	0.78	0.78	0	0	1
25249	84155	6	4	0	0	0	0	1	1	1	3	0	0.73	0.78	1	0	1
25250	84168	5	12	0	1	1	1	0	0	0	0	0	0.73	0.79	0	1	1
25251	84170	425	2	108	0	142	419	83	286	455	465	0	0.96	0.96	0	0	1

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Spearman's ρ

Pearson's r

Kendall's τ

Cramér's V (φc)

Phik (φk)

Missing values

Sample

First rows

Last rows